The rapid pace of technological innovation seen over the past decade has significantly reshaped the modern employment landscape, with the push for greater automation and data-driven workflows creating a high demand for tech savvy workers. This shift toward information-driven frameworks has been called the "Fourth Industrial Revolution" by a number of influential business leaders - a concept that took center stage during the 2019 World Economic Forum - but transitioning to an AI-driven workforce won't happen overnight. That said, organizations in nearly every industry are taking steps to prepare for the future of work by seeking out talented candidates who possess the right set of technical skills and a willingness to adapt to new operational models.
The widespread use of software-embedded machine learning and data analysis tools is already having a notable impact on hiring trends. According to the WEF's 2018 Job Report, technology-augmented work is expected to expand across every employment sector between 2018 to 2022, with high-speed mobile internet, artificial intelligence, cloud technology and big data analytics serving as the key drivers of change. As companies become more reliant on these technologies, the need for a data-literate workforce will grow increasingly important. But what is data literacy, exactly?
The importance of data literacy
Simply put, data literacy is the ability to extract information and actionable insights from data. While computer skills are essential to this process, it also involves a good deal of analytical prowess. The employees of the future will need to isolate valuable data, examine complex interrelationships and formulate creative solutions based on their digital research. According to TechTarget, data literacy skills include the ability to:
- Evaluate the relevance of data in specific operational scenarios
- Think critically about how extracted information can be applied
- Interpret data visualizations like graphs, charts and tables
- Recognize when data is misrepresented or used to mislead
- Communicate effectively with peers who lack data literacy
Data-driven decision making will eventually become the new norm for businesses around the world, but preparing for this change takes time. Employers may benefit from building a strong foundation for their data-literate workforce as soon as possible, as waiting too can lead to missed opportunities.
Tips for hiring data literate employees
According to a recent study from Gartner, an estimated 50% of organizations will lack the essential AI and data literacy skills they need to create new business value by 2020. Additionally, researchers expect that 80% of all organizations will have to implement competency development programs to overcome their data literacy deficiencies. However, employers still have time to attract talented employees with the knowledge, experience and proficiency they need to excel in an information-driven economy. To help you get started, here are three tips for hiring data-literate employees:
- Prioritize analytical skills: Candidates who possess advanced critical thinking and logical assessment competencies will be essential to your operational success. Hiring managers can incorporate skills testing into their recruitment process to identify job seekers with above average analytical capabilities.
- Verify technical experience: Most applicants include a range of computer-based skills on their resume, but this doesn't mean they have high-level experience with the data analysis software your company uses. Consulting with tech-savvy employees can help you create a list of targeted questions that may be relevant during the interview process.
- Assess cognitive abilities: A candidate's capacity to think, read, learn and reason when presented with complex information can give you a sense of their data literacy, which is why skills assessment software can be such a valuable recruitment tool. Job seekers with strong interpersonal skills can often seem like the perfect fit, but analyzing data requires a lot more than personality.
As the lines between information gathering and automation continue to blur, companies will increasingly depend on a data literate workforce to remain stable, competitive and profitable.